chore: import upstream snapshot with attribution
This commit is contained in:
wehub-resource-sync
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"""
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Samplesheet validation utilities.
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Validates samplesheet rows against pipeline configuration before writing,
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catching errors early with helpful messages.
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"""
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import os
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from dataclasses import dataclass, field
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from pathlib import Path
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from typing import Dict, List, Optional
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import yaml
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@dataclass
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class ValidationResult:
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"""Result of samplesheet validation."""
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valid: bool
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errors: List[str] = field(default_factory=list)
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warnings: List[str] = field(default_factory=list)
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suggestions: List[str] = field(default_factory=list)
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def __bool__(self):
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return self.valid
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def summary(self) -> str:
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"""Generate human-readable summary."""
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lines = []
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if self.errors:
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lines.append("Errors:")
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for e in self.errors:
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lines.append(f" - {e}")
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if self.warnings:
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lines.append("Warnings:")
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for w in self.warnings:
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lines.append(f" - {w}")
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if self.suggestions:
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lines.append("Suggestions:")
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for s in self.suggestions:
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lines.append(f" - {s}")
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return "\n".join(lines)
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def load_pipeline_config(pipeline: str) -> Optional[Dict]:
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"""Load pipeline configuration from YAML file."""
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# Find config directory relative to this file
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script_dir = Path(__file__).parent.parent.parent
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config_path = script_dir / "config" / "pipelines" / f"{pipeline}.yaml"
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if not config_path.exists():
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return None
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with open(config_path) as f:
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return yaml.safe_load(f)
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def validate_samplesheet(
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rows: List[Dict],
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pipeline: str,
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config: Optional[Dict] = None
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) -> ValidationResult:
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"""
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Validate samplesheet rows against pipeline requirements.
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Args:
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rows: List of row dictionaries
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pipeline: Pipeline name (e.g., 'rnaseq', 'sarek')
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config: Optional pre-loaded config dict
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Returns:
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ValidationResult with errors, warnings, and suggestions
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"""
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errors = []
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warnings = []
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suggestions = []
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# Load config if not provided
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if config is None:
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config = load_pipeline_config(pipeline)
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if config is None:
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errors.append(f"Unknown pipeline: {pipeline}")
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return ValidationResult(valid=False, errors=errors)
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columns = config.get("samplesheet", {}).get("columns", [])
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required_cols = [c["name"] for c in columns if c.get("required", False)]
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if not rows:
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errors.append("Samplesheet is empty - no samples found")
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return ValidationResult(valid=False, errors=errors)
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# Validate each row
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for i, row in enumerate(rows):
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row_num = i + 2 # Account for header row
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# Check required columns
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for col_name in required_cols:
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col_config = next((c for c in columns if c["name"] == col_name), None)
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# Skip columns with conditions that don't apply
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if col_config and "condition" in col_config:
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# Simple condition check - skip for now
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# Full implementation would evaluate conditions
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pass
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if col_name not in row or row[col_name] is None or row[col_name] == "":
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# Check if there's a default
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if col_config and "default" in col_config:
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continue
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errors.append(f"Row {row_num}: Missing required column '{col_name}'")
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# Validate path columns exist
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for col_name in ["fastq_1", "fastq_2", "bam", "bai"]:
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if col_name in row and row[col_name]:
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path = row[col_name]
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if not os.path.exists(path):
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errors.append(f"Row {row_num}: File not found: {path}")
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elif not os.path.isfile(path):
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errors.append(f"Row {row_num}: Not a file: {path}")
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# Validate enum values
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for col_config in columns:
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col_name = col_config["name"]
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if col_name in row and row[col_name] and "allowed" in col_config:
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value = row[col_name]
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allowed = col_config["allowed"]
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if value not in allowed:
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errors.append(
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f"Row {row_num}: Invalid value '{value}' for '{col_name}'. "
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f"Allowed: {allowed}"
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)
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# Check R1/R2 pairing consistency
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r1 = row.get("fastq_1", "")
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r2 = row.get("fastq_2", "")
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if r1 and not r2:
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warnings.append(f"Row {row_num}: Single-end data (no R2 file)")
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elif r2 and not r1:
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errors.append(f"Row {row_num}: R2 present but R1 missing")
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# Check for duplicate samples
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sample_col = "sample" if "sample" in rows[0] else "patient"
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if sample_col in rows[0]:
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samples = [r.get(sample_col, "") for r in rows]
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duplicates = [s for s in set(samples) if samples.count(s) > 1]
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if duplicates:
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warnings.append(f"Duplicate sample names: {duplicates}")
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suggestions.append(
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"Duplicates may be intentional (multi-lane sequencing). "
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"Verify sample grouping is correct."
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)
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# Pipeline-specific validation
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if pipeline == "sarek":
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_validate_sarek_specific(rows, errors, warnings, suggestions)
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elif pipeline == "atacseq":
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_validate_atacseq_specific(rows, errors, warnings, suggestions)
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return ValidationResult(
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valid=len(errors) == 0,
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errors=errors,
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warnings=warnings,
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suggestions=suggestions
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)
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def _validate_sarek_specific(
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rows: List[Dict],
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errors: List[str],
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warnings: List[str],
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suggestions: List[str]
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):
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"""Sarek-specific validation for tumor/normal pairing."""
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# Group by patient
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patients = {}
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for row in rows:
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patient = row.get("patient", "")
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status = row.get("status")
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if patient not in patients:
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patients[patient] = {"tumor": 0, "normal": 0, "unknown": 0}
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if status == 1:
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patients[patient]["tumor"] += 1
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elif status == 0:
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patients[patient]["normal"] += 1
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else:
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patients[patient]["unknown"] += 1
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# Check pairing
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for patient, counts in patients.items():
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if counts["tumor"] > 0 and counts["normal"] == 0:
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warnings.append(
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f"Patient '{patient}': Tumor sample(s) without matched normal. "
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"Somatic calling works best with paired tumor-normal."
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)
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suggestions.append(
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f"For patient '{patient}': Add a normal sample or use tumor-only mode."
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)
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if counts["unknown"] > 0:
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warnings.append(
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f"Patient '{patient}': {counts['unknown']} sample(s) with unknown status. "
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"Set status column to 0 (normal) or 1 (tumor)."
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)
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def _validate_atacseq_specific(
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rows: List[Dict],
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errors: List[str],
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warnings: List[str],
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suggestions: List[str]
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):
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"""ATAC-seq specific validation for replicates."""
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# Group by sample (condition)
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samples = {}
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for row in rows:
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sample = row.get("sample", "")
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replicate = row.get("replicate", 1)
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if sample not in samples:
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samples[sample] = []
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samples[sample].append(replicate)
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# Check replicates
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for sample, reps in samples.items():
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if len(reps) < 2:
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warnings.append(
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f"Sample '{sample}': Only {len(reps)} replicate(s). "
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"Consensus peaks require 2+ replicates."
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)
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# Check for duplicate replicate numbers
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if len(reps) != len(set(reps)):
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errors.append(
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f"Sample '{sample}': Duplicate replicate numbers detected. "
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"Each replicate must have a unique number."
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)
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# Check all samples have R2 (ATAC-seq requires paired-end)
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for i, row in enumerate(rows):
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if not row.get("fastq_2"):
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errors.append(
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f"Row {i+2}: ATAC-seq requires paired-end data. R2 file missing."
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)
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def validate_file_exists(path: str) -> bool:
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"""Check if file exists and is accessible."""
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return os.path.isfile(path) and os.access(path, os.R_OK)
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def validate_absolute_path(path: str) -> bool:
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"""Check if path is absolute."""
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return os.path.isabs(path)
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